A platform for computationally advanced collaborative agroinformatics data discovery and analysis

Andrew Gustafson, Jesse Erdmann, Michael Milligan, Getiria Onsongo, Philip Pardey, Tom Prather, Kevin Silverstein, James Wilgenbusch, Ying Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The International Agroinformatics Alliance (IAA) is a coalition of public and private institutions that are cooperating to develop a platform for computationally advanced collaborative analysis of agricultural data. By combining large agricultural data sets with advanced analysis techniques, IAA seeks to catalyze agricultural research, leading to improved agricultural productivity and stability. IAA has constructed a platform that combines Jupyterhub web notebooks for interactive data analysis, relational databases for storage of crop genetic and geospatial data, and the Globus file transfer system for efficient data transfer and authentication. The platform uses a data permissions system that allows users to share data with collaborators. The central platform is located at the Minnesota Supercomputing Institute, at the University of Minnesota, which allows access to the large storage and compute resources required for advanced agroinformatics analysis pipelines.

Original languageEnglish (US)
Title of host publicationPEARC 2017 - Practice and Experience in Advanced Research Computing 2017
Subtitle of host publicationSustainability, Success and Impact
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450352727
DOIs
StatePublished - Jul 9 2017
Event2017 Practice and Experience in Advanced Research Computing, PEARC 2017 - New Orleans, United States
Duration: Jul 9 2017Jul 13 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128771

Other

Other2017 Practice and Experience in Advanced Research Computing, PEARC 2017
CountryUnited States
CityNew Orleans
Period7/9/177/13/17

    Fingerprint

Cite this

Gustafson, A., Erdmann, J., Milligan, M., Onsongo, G., Pardey, P., Prather, T., Silverstein, K., Wilgenbusch, J., & Zhang, Y. (2017). A platform for computationally advanced collaborative agroinformatics data discovery and analysis. In PEARC 2017 - Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact [a2] (ACM International Conference Proceeding Series; Vol. Part F128771). Association for Computing Machinery. https://doi.org/10.1145/3093338.3093376